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def transpose(matrix):
rows = len(matrix)
columns = len(matrix[0])
matrix_T = []
for j in range(columns):
row = []
for i in range(rows):
row.append(matrix[i][j])
matrix_T.append(row)
return matrix_T
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>>> a = np.array([[1, 2], [3, 4]])
>>> a
array([[1, 2],
[3, 4]])
>>> a.transpose()
array([[1, 3],
[2, 4]])
>>> a.transpose((1, 0))
array([[1, 3],
[2, 4]])
>>> a.transpose(1, 0)
array([[1, 3],
[2, 4]])
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import numpy as np
A = [1, 2, 3, 4]
np.array(A).T # .T is used to transpose matrix
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ndarray.T
x = np.array([[1.,2.],[3.,4.]])
>>> x
array([[ 1., 2.],
[ 3., 4.]])
>>> x.T
array([[ 1., 3.],
[ 2., 4.]])
>>> x = np.array([1.,2.,3.,4.])
>>> x
array([ 1., 2., 3., 4.])
>>> x.T
array([ 1., 2., 3., 4.])
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>>> import numpy as np
>>> M = np.array([[1,2,3],[4,5,6],[7,8,9]])
>>> M
array([[1, 2, 3],
[4, 5, 6],
[7, 8, 9]])
>>> M.T
array([[1, 4, 7],
[2, 5, 8],
[3, 6, 9]])